Evidence map›Paper›PMID 39452626›Full record

ArticleJournal of fungi (Basel, Switzerland)2024

Predicting Fungemia in the ICU: Unveiling the Value of Weekly Fungal Surveillance and Yeast Colonisation Monitoring.

Pedro Suárez-Urquiza, Javier Pemán, Monica Gordon, Patricio Favier, Paula Muñoz-Brell, Jose Luis López-Hontangas, Alba Ruiz-Gaitán

Abstract read
In one paragraph

Article in Journal of fungi (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Active Screening forJournal of fungi (Basel, Switzerland) · 2026
    Review
  2. Article
  3. International journal of molecular sciences · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Pedro Suárez-UrquizaDepartment of Medical Microbiology, University and Polytechnic La Fe Hospital, 46026 Valencia, Spain.ORCID 0000-0001-5774-4156
Javier PemánDepartment of Medical Microbiology, University and Polytechnic La Fe Hospital, 46026 Valencia, Spain.
Monica GordonDepartment of Intensive Care Unit, University and Polytechnic La Fe Hospital, 46026 Valencia, Spain.ORCID 0000-0003-1630-2276
Patricio FavierDepartment of Medical Microbiology, University and Polytechnic La Fe Hospital, 46026 Valencia, Spain.
Paula Muñoz-BrellDepartment of Medical Microbiology, University and Polytechnic La Fe Hospital, 46026 Valencia, Spain.
Jose Luis López-HontangasDepartment of Medical Microbiology, University and Polytechnic La Fe Hospital, 46026 Valencia, Spain.ORCID 0000-0003-1426-3672
Alba Ruiz-GaitánDepartment of Medical Microbiology, University and Polytechnic La Fe Hospital, 46026 Valencia, Spain.ORCID 0000-0003-1730-9947

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fungemia remains a major threat in intensive care units (ICUs), with high mortality rates despite advances in diagnostics and treatment. Colonisation by yeasts is an independent risk factor for fungemia; however, its predictive utility requires further research. In this 8-year study, we analysed 38,017 samples from 3206 patients and 171 fungemia episodes as part of a weekly fungal surveillance programme. We evaluated species-specific colonisation patterns, the predictive value of the Colonisation Index (CI) and Corrected Colonisation Index (CCI), and candidemia risks associated with different yeast species and anatomical site colonisation. Our results showed that

Indexed as

Candida auriscandidemiacandidemia predictorscolonisationintensive care unitsurveillance

Identifiers

PMID39452626
PMCPMC11508630

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.